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bert-finetuned-ner-clinical-plncmm-8
This model is a fine-tuned version of plncmm/beto-clinical-wl-es on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.2568
- Precision: 0.7476
- Recall: 0.8063
- F1: 0.7758
- Accuracy: 0.9277
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 3e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 3
Training results
Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
---|---|---|---|---|---|---|---|
0.6628 | 1.0 | 502 | 0.2590 | 0.6791 | 0.7711 | 0.7222 | 0.9103 |
0.2168 | 2.0 | 1004 | 0.2309 | 0.7243 | 0.7975 | 0.7591 | 0.9238 |
0.1301 | 3.0 | 1506 | 0.2568 | 0.7476 | 0.8063 | 0.7758 | 0.9277 |
Framework versions
- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3